In this paper, after briefly considering the reasons that prevented the development of hybrid systems for signal processing (SP), we point out the requirements for their future exploitation. The need for a better knowledge of different approaches in the scientific community and the definition of methodologies for designing hybrid systems' are highlighted as two key points. Then we suggest that the well-blown ''task-structure analysis'' design technique should be modified to make it suitable for hybrid systems. The proposed modification is based on the main need to choose the roles of different approaches and the mechanisms to integrate them. As an example, we describe the design of a hybrid system for two-dimensional (2 D) image recognition; the system is based on the integration of a numerical, a symbolic, and a connectionist approach. We detail the integration of the symbolic and connectionist approaches to the generation of the models of the objects to be recognized. We describe the main problems involved and the solutions adopted. In particular, we exploit the synergistic aspects of the two approaches in oi dei to overcome the bottleneck of knowledge acquisition. Finally, we report experimental results on two applications to show some advantages of the proposed hybrid system.
A hybrid system for two-dimensional image recognition
ROLI, FABIO;
1995-01-01
Abstract
In this paper, after briefly considering the reasons that prevented the development of hybrid systems for signal processing (SP), we point out the requirements for their future exploitation. The need for a better knowledge of different approaches in the scientific community and the definition of methodologies for designing hybrid systems' are highlighted as two key points. Then we suggest that the well-blown ''task-structure analysis'' design technique should be modified to make it suitable for hybrid systems. The proposed modification is based on the main need to choose the roles of different approaches and the mechanisms to integrate them. As an example, we describe the design of a hybrid system for two-dimensional (2 D) image recognition; the system is based on the integration of a numerical, a symbolic, and a connectionist approach. We detail the integration of the symbolic and connectionist approaches to the generation of the models of the objects to be recognized. We describe the main problems involved and the solutions adopted. In particular, we exploit the synergistic aspects of the two approaches in oi dei to overcome the bottleneck of knowledge acquisition. Finally, we report experimental results on two applications to show some advantages of the proposed hybrid system.
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